Camillo Porcaro - Academia.edu (original) (raw)
Papers by Camillo Porcaro
In this paper, we apply independent component analysis to fetal magnetocardiographic data. In par... more In this paper, we apply independent component analysis to fetal magnetocardiographic data. In particular, we propose an extension of the "cumulant-based iterative inversion" algorithm to include a two-step "signal subspace" subdivision, which allows the user to control the number of components to be estimated by analyzing the eigenvalues distribution in an interactive way. Our results show that this method is a powerful means not only for the extraction of the cardiac signals from the background noise but also for a sharp separation of the baby's heart from the mother's.
Journal of neurology, 2015
Fatigue in multiple sclerosis (MS) is a highly disabling symptom. Among the central mechanisms be... more Fatigue in multiple sclerosis (MS) is a highly disabling symptom. Among the central mechanisms behind it, an involvement of sensorimotor networks is clearly evident from structural and functional studies. We aimed at assessing whether functional/structural balances of homologous sensorimotor regions-known to be crucial for sensorimotor networks effectiveness-decrease with MS fatigue increase. Functional connectivity measures at rest and during a simple motor task (weak handgrip of either the right or left hand) were derived from primary sensorimotor areas electroencephalographic recordings in 27 mildly disabled MS patients. Structural MRI-derived inter-hemispheric asymmetries included the cortical thickness of Rolandic regions and the volume of thalami. Fatigue symptoms increased together with the functional inter-hemispheric imbalance of sensorimotor homologous areas activities at rest and during movement, in absence of any appreciable parenchymal asymmetries. This finding supports...
A brain-computer interface (BCI) can be defined as any system that can track the person's intent ... more A brain-computer interface (BCI) can be defined as any system that can track the person's intent which is embedded in his/her brain activity and, from it alone, translate the intention into commands of a computer. Among the brain signal monitoring systems best suited for this challenging task, electroencephalography (EEG) and magnetoencephalography (MEG) are the most realistic, since both are non-invasive, EEG is portable and MEG could provide more specific information that could be later exploited also through EEG signals. The first two BCI steps require set up of the appropriate experimental protocol while recording the brain signal and then to extract interesting features from the recorded cerebral activity. To provide information useful in these BCI stages, our aim is to provide an overview of a new procedure we recently developed, named functional source separation (FSS). As it comes from the blind source separation algorithms, it exploits the most valuable information provided by the electrophysiological techniques, i.e. the waveform signal properties, remaining blind to the biophysical nature of the signal sources. FSS returns the single trial source activity, estimates the time course of a neuronal pool along different experimental states on the basis of a specific functional requirement in a specific time period, and uses the simulated annealing as the optimization procedure allowing the exploit of functional constraints non-differentiable. Moreover, a minor section is included, devoted to information acquired by MEG in stroke patients, to guide BCI applications aiming at sustaining motor behaviour in these patients. Relevant BCI featuresspatial and time-frequency properties -are in fact altered by a stroke in the regions devoted to hand control. Moreover, a method to investigate the relationship between sensory and motor hand cortical network activities is described, providing information useful to develop BCI feedback control systems. This review provides a description of the FSS technique, a promising tool for the BCI community for online electrophysiological feature extraction, and offers interesting information to develop BCI applications to sustain hand control in stroke patients.
NeuroImage, 2013
The human brain is continually, dynamically active and spontaneous fluctuations in this activity ... more The human brain is continually, dynamically active and spontaneous fluctuations in this activity play a functional role in affecting both behavioural and neuronal responses. However, the mechanisms through which this occurs remain poorly understood. Simultaneous EEG-fMRI is a promising technique to study how spontaneous activity modulates the brain's response to stimulation, as temporal indices of ongoing cortical excitability can be integrated with spatially localised evoked responses. Here we demonstrate an interaction between the ongoing power of the electrophysiological alpha oscillation and the magnitude of both positive (PBR) and negative (NBR) fMRI responses to two contrasts of visual checkerboard reversal. Furthermore, the amplitude of pre-stimulus EEG alpha-power significantly modulated the amplitude and shape of subsequent PBR and NBR to the visual stimulus. A nonlinear reduction of visual PBR and an enhancement of auditory NBR and default-mode network NBR were observe...
Neuroimage, 2009
A wide range of essential reasoning tasks rely on contradiction identification, a cornerstone of ... more A wide range of essential reasoning tasks rely on contradiction identification, a cornerstone of human rationality, communication and debate founded on the inversion of the logical operators ''Every'' and ''Some.'' A high-density electroencephalographic (EEG) study was performed in 11 normal young adults. The cerebral network involved in the identification of contradiction included the orbito-frontal and anterior-cingulate cortices and the temporo-polar cortices. The event-related dynamic of this network showed an early negative deflection lasting 500 ms after sentence presentation. This was followed by a positive deflection lasting 1.5 s, which was different for the two logical operators. A lesser degree of network activation (either in neuron number or their level of phase locking or both) occurred while processing statements with ''Some,'' suggesting that this was a relatively simpler scenario with one example to be figured out, instead of the many examples or the absence of a counterexample searched for while processing statements with ''Every.'' A self-generated reward system seemed to resonate the recruited circuitry when the contradictory task is successfully completed. Hum Brain Mapp 30:4187-4197, 2009. V C 2009 Wiley-Liss, Inc.
Signals and Communication Technology, 2014
Neuroimaging, investigating how specific brain sources play a particular 1 role in a definite cog... more Neuroimaging, investigating how specific brain sources play a particular 1 role in a definite cognitive or sensorimotor process, can be achieved from 2 non-invasive electrophysiological (EEG, EMG, MEG) and multimodal (concurrent 3 EEG-fMRI) recordings. However, especially for the non-invasive electrophysiolog-4 ical techniques, the signals measured at the scalp are a mixture of the contributions 5 from multiple generators or sources added to background activity and system noise, 6 meaning that it is often difficult to identify the dynamic activity of generators of inter-7 est starting from the electrode/sensor recordings. Although the most common method 8 of overcoming this limitation is time-domain averaging with or without source local-9
NeuroImage, 2011
We have recently proposed the evaluation of a set of information theoretic quantities (ITQs) for ... more We have recently proposed the evaluation of a set of information theoretic quantities (ITQs) for the integration of simultaneously acquired EEG-fMRI data (Ostwald, D., Porcaro, C., Bagshaw, A.P., 2010. An information theoretic approach to EEG-fMRI integration of visually evoked responses. Neuroimage. 49,[498][499][500][501][502][503][504][505][506][507][508][509][510][511][512][513][514][515][516]. In our previous experimental evaluation of the information theoretic framework, we defined the data subsets from which to calculate the ITQs using a priori constraints. In the case of EEG, this meant that data were extracted from a single electrode, while for fMRI the analysed data came from voxels contained within a sphere surrounding the most responsive voxel of visual cortex. While this approach was a natural starting point for the evaluation of the framework in the application to combined EEG-fMRI data sets, a more principled approach to data selection is desirable. Here, we propose to combine standard fMRI data preprocessing and low-resolution electromagnetic tomography (LORETA) for the evaluation of ITQs across the entire three-dimensional brain space. We apply the proposed method to a simultaneous EEG-fMRI data set acquired during checkerboard stimulation and assess the topographical informativeness of EEG (time and frequency domain) and fMRI features with respect to the stimulus and each other. The resulting information theoretic effect size maps are supplemented with a statistical evaluation based on Gaussian null model simulations using a false-discovery rate procedure. Given the contamination of EEG recordings by artefacts induced by the MR scanning environment we further assessed the influence of different advanced EEG preprocessing methods (independent component analysis and functional source separation) on the information topography. The results of this analysis provide evidence for the topographically focussed informativeness of both EEG and fMRI features with respect to the stimulus, but for the current feature selection do not detect EEG-fMRI activity dependence. More advanced EEG data pre-processing rendered the feature distributions more stimulus-informative, but did not alter the EEG-fMRI activity and conditional dependencies.
Lecture Notes in Computer Science, 2004
ABSTRACT In this paper we apply Independent Component Analysis to magnetocardiographic data recor... more ABSTRACT In this paper we apply Independent Component Analysis to magnetocardiographic data recorded from the abdomen of pregnant women. In particular, we include a dimensionality reduction in the ’Cumulant Based Iterative Inversion’ algorithm to achieve a ’signal subspace’ subdivision, which enhances the algorithm’s efficacy in resolving the signals of interest from the recorded traces. Our results show that the proposed two-step procedure is a powerful means for the extraction of the cardiac signals from the background noise and for a sharp separation of the baby’s heart from the mother’s.
Purpose: This work investigates how a direct bidirectional connection between brain and hand pros... more Purpose: This work investigates how a direct bidirectional connection between brain and hand prosthesis modifies the bi-hemispheric sensorimotor system devoted to the movement control of the lost limb. Hand prostheses are often unable to satisfy users' expectations, mostly due to the poor performance of their interfacing system. Neural Interfaces implanted inside nerves of the stump offer the advantage of using the bidirectional neural pathways 'naturally' dispatching signals to control proper hand actions and feed-back sensations. Learning to control a neurally-interfaced hand prosthesis and decode sensory information was previously observed to reduce the inter-hemispheric asymmetry of cortical motor maps and the clinical symptoms of phantom limb syndrome. Methods: Electroencephalographic (EEG) data was analysed using Functional Source Separation (FSS), a semi-blind method that incorporates prior knowledge about the signal of interest into data decomposition to give access to cortical patch activities. Results: Bi-hemispheric cortices showed normalization of their activity (topographical and spectral patterns) and of functional connectivity between homologous hand controlling areas, during the delivery of the motor command to the cybernetic prosthesis. Conclusions: The re-establishment of central-peripheral communication with the lost limb induced by a neurally-interfaced hand prosthesis produces beneficial plastic reorganization, not only restructuring contralateral directly-connected control areas, but also their functional balance within the bi-hemispheric system necessary for motor control. and the integrity of cutaneous/proprioceptive sensory organs. Brain Machine Interfaces (BMI) bypass the above steps and allow motor signals to be picked up directly from the nervous system and relayed to an external electronic or robotic effector which physically performs the subject's motor intention and plans. In addition to facilitating extraction of motor volition, bidirectional BMIs also create the capacity to manage neural signal flows in both afferent and efferent directions.
The Journal of Physiology, 2007
A brain-computer interface (BCI) can be defined as any system that can track the person's intent ... more A brain-computer interface (BCI) can be defined as any system that can track the person's intent which is embedded in his/her brain activity and, from it alone, translate the intention into commands of a computer. Among the brain signal monitoring systems best suited for this challenging task, electroencephalography (EEG) and magnetoencephalography (MEG) are the most realistic, since both are non-invasive, EEG is portable and MEG could provide more specific information that could be later exploited also through EEG signals. The first two BCI steps require set up of the appropriate experimental protocol while recording the brain signal and then to extract interesting features from the recorded cerebral activity. To provide information useful in these BCI stages, our aim is to provide an overview of a new procedure we recently developed, named functional source separation (FSS). As it comes from the blind source separation algorithms, it exploits the most valuable information provided by the electrophysiological techniques, i.e. the waveform signal properties, remaining blind to the biophysical nature of the signal sources. FSS returns the single trial source activity, estimates the time course of a neuronal pool along different experimental states on the basis of a specific functional requirement in a specific time period, and uses the simulated annealing as the optimization procedure allowing the exploit of functional constraints non-differentiable. Moreover, a minor section is included, devoted to information acquired by MEG in stroke patients, to guide BCI applications aiming at sustaining motor behaviour in these patients. Relevant BCI featuresspatial and time-frequency properties -are in fact altered by a stroke in the regions devoted to hand control. Moreover, a method to investigate the relationship between sensory and motor hand cortical network activities is described, providing information useful to develop BCI feedback control systems. This review provides a description of the FSS technique, a promising tool for the BCI community for online electrophysiological feature extraction, and offers interesting information to develop BCI applications to sustain hand control in stroke patients.
NeuroImage, 2008
Sensory feedback in motor control is widely recognized to be the key link between the activity of... more Sensory feedback in motor control is widely recognized to be the key link between the activity of the primary motor cortex to the motor behavior.
Clinical Neurophysiology, 2010
Clinical Neurophysiology, 2010
Clinical Neurophysiology, 2010
Clinical Neurophysiology, 2011
Clinical Neurophysiology, 2010
In this paper, we apply independent component analysis to fetal magnetocardiographic data. In par... more In this paper, we apply independent component analysis to fetal magnetocardiographic data. In particular, we propose an extension of the "cumulant-based iterative inversion" algorithm to include a two-step "signal subspace" subdivision, which allows the user to control the number of components to be estimated by analyzing the eigenvalues distribution in an interactive way. Our results show that this method is a powerful means not only for the extraction of the cardiac signals from the background noise but also for a sharp separation of the baby's heart from the mother's.
Journal of neurology, 2015
Fatigue in multiple sclerosis (MS) is a highly disabling symptom. Among the central mechanisms be... more Fatigue in multiple sclerosis (MS) is a highly disabling symptom. Among the central mechanisms behind it, an involvement of sensorimotor networks is clearly evident from structural and functional studies. We aimed at assessing whether functional/structural balances of homologous sensorimotor regions-known to be crucial for sensorimotor networks effectiveness-decrease with MS fatigue increase. Functional connectivity measures at rest and during a simple motor task (weak handgrip of either the right or left hand) were derived from primary sensorimotor areas electroencephalographic recordings in 27 mildly disabled MS patients. Structural MRI-derived inter-hemispheric asymmetries included the cortical thickness of Rolandic regions and the volume of thalami. Fatigue symptoms increased together with the functional inter-hemispheric imbalance of sensorimotor homologous areas activities at rest and during movement, in absence of any appreciable parenchymal asymmetries. This finding supports...
A brain-computer interface (BCI) can be defined as any system that can track the person's intent ... more A brain-computer interface (BCI) can be defined as any system that can track the person's intent which is embedded in his/her brain activity and, from it alone, translate the intention into commands of a computer. Among the brain signal monitoring systems best suited for this challenging task, electroencephalography (EEG) and magnetoencephalography (MEG) are the most realistic, since both are non-invasive, EEG is portable and MEG could provide more specific information that could be later exploited also through EEG signals. The first two BCI steps require set up of the appropriate experimental protocol while recording the brain signal and then to extract interesting features from the recorded cerebral activity. To provide information useful in these BCI stages, our aim is to provide an overview of a new procedure we recently developed, named functional source separation (FSS). As it comes from the blind source separation algorithms, it exploits the most valuable information provided by the electrophysiological techniques, i.e. the waveform signal properties, remaining blind to the biophysical nature of the signal sources. FSS returns the single trial source activity, estimates the time course of a neuronal pool along different experimental states on the basis of a specific functional requirement in a specific time period, and uses the simulated annealing as the optimization procedure allowing the exploit of functional constraints non-differentiable. Moreover, a minor section is included, devoted to information acquired by MEG in stroke patients, to guide BCI applications aiming at sustaining motor behaviour in these patients. Relevant BCI featuresspatial and time-frequency properties -are in fact altered by a stroke in the regions devoted to hand control. Moreover, a method to investigate the relationship between sensory and motor hand cortical network activities is described, providing information useful to develop BCI feedback control systems. This review provides a description of the FSS technique, a promising tool for the BCI community for online electrophysiological feature extraction, and offers interesting information to develop BCI applications to sustain hand control in stroke patients.
NeuroImage, 2013
The human brain is continually, dynamically active and spontaneous fluctuations in this activity ... more The human brain is continually, dynamically active and spontaneous fluctuations in this activity play a functional role in affecting both behavioural and neuronal responses. However, the mechanisms through which this occurs remain poorly understood. Simultaneous EEG-fMRI is a promising technique to study how spontaneous activity modulates the brain's response to stimulation, as temporal indices of ongoing cortical excitability can be integrated with spatially localised evoked responses. Here we demonstrate an interaction between the ongoing power of the electrophysiological alpha oscillation and the magnitude of both positive (PBR) and negative (NBR) fMRI responses to two contrasts of visual checkerboard reversal. Furthermore, the amplitude of pre-stimulus EEG alpha-power significantly modulated the amplitude and shape of subsequent PBR and NBR to the visual stimulus. A nonlinear reduction of visual PBR and an enhancement of auditory NBR and default-mode network NBR were observe...
Neuroimage, 2009
A wide range of essential reasoning tasks rely on contradiction identification, a cornerstone of ... more A wide range of essential reasoning tasks rely on contradiction identification, a cornerstone of human rationality, communication and debate founded on the inversion of the logical operators ''Every'' and ''Some.'' A high-density electroencephalographic (EEG) study was performed in 11 normal young adults. The cerebral network involved in the identification of contradiction included the orbito-frontal and anterior-cingulate cortices and the temporo-polar cortices. The event-related dynamic of this network showed an early negative deflection lasting 500 ms after sentence presentation. This was followed by a positive deflection lasting 1.5 s, which was different for the two logical operators. A lesser degree of network activation (either in neuron number or their level of phase locking or both) occurred while processing statements with ''Some,'' suggesting that this was a relatively simpler scenario with one example to be figured out, instead of the many examples or the absence of a counterexample searched for while processing statements with ''Every.'' A self-generated reward system seemed to resonate the recruited circuitry when the contradictory task is successfully completed. Hum Brain Mapp 30:4187-4197, 2009. V C 2009 Wiley-Liss, Inc.
Signals and Communication Technology, 2014
Neuroimaging, investigating how specific brain sources play a particular 1 role in a definite cog... more Neuroimaging, investigating how specific brain sources play a particular 1 role in a definite cognitive or sensorimotor process, can be achieved from 2 non-invasive electrophysiological (EEG, EMG, MEG) and multimodal (concurrent 3 EEG-fMRI) recordings. However, especially for the non-invasive electrophysiolog-4 ical techniques, the signals measured at the scalp are a mixture of the contributions 5 from multiple generators or sources added to background activity and system noise, 6 meaning that it is often difficult to identify the dynamic activity of generators of inter-7 est starting from the electrode/sensor recordings. Although the most common method 8 of overcoming this limitation is time-domain averaging with or without source local-9
NeuroImage, 2011
We have recently proposed the evaluation of a set of information theoretic quantities (ITQs) for ... more We have recently proposed the evaluation of a set of information theoretic quantities (ITQs) for the integration of simultaneously acquired EEG-fMRI data (Ostwald, D., Porcaro, C., Bagshaw, A.P., 2010. An information theoretic approach to EEG-fMRI integration of visually evoked responses. Neuroimage. 49,[498][499][500][501][502][503][504][505][506][507][508][509][510][511][512][513][514][515][516]. In our previous experimental evaluation of the information theoretic framework, we defined the data subsets from which to calculate the ITQs using a priori constraints. In the case of EEG, this meant that data were extracted from a single electrode, while for fMRI the analysed data came from voxels contained within a sphere surrounding the most responsive voxel of visual cortex. While this approach was a natural starting point for the evaluation of the framework in the application to combined EEG-fMRI data sets, a more principled approach to data selection is desirable. Here, we propose to combine standard fMRI data preprocessing and low-resolution electromagnetic tomography (LORETA) for the evaluation of ITQs across the entire three-dimensional brain space. We apply the proposed method to a simultaneous EEG-fMRI data set acquired during checkerboard stimulation and assess the topographical informativeness of EEG (time and frequency domain) and fMRI features with respect to the stimulus and each other. The resulting information theoretic effect size maps are supplemented with a statistical evaluation based on Gaussian null model simulations using a false-discovery rate procedure. Given the contamination of EEG recordings by artefacts induced by the MR scanning environment we further assessed the influence of different advanced EEG preprocessing methods (independent component analysis and functional source separation) on the information topography. The results of this analysis provide evidence for the topographically focussed informativeness of both EEG and fMRI features with respect to the stimulus, but for the current feature selection do not detect EEG-fMRI activity dependence. More advanced EEG data pre-processing rendered the feature distributions more stimulus-informative, but did not alter the EEG-fMRI activity and conditional dependencies.
Lecture Notes in Computer Science, 2004
ABSTRACT In this paper we apply Independent Component Analysis to magnetocardiographic data recor... more ABSTRACT In this paper we apply Independent Component Analysis to magnetocardiographic data recorded from the abdomen of pregnant women. In particular, we include a dimensionality reduction in the ’Cumulant Based Iterative Inversion’ algorithm to achieve a ’signal subspace’ subdivision, which enhances the algorithm’s efficacy in resolving the signals of interest from the recorded traces. Our results show that the proposed two-step procedure is a powerful means for the extraction of the cardiac signals from the background noise and for a sharp separation of the baby’s heart from the mother’s.
Purpose: This work investigates how a direct bidirectional connection between brain and hand pros... more Purpose: This work investigates how a direct bidirectional connection between brain and hand prosthesis modifies the bi-hemispheric sensorimotor system devoted to the movement control of the lost limb. Hand prostheses are often unable to satisfy users' expectations, mostly due to the poor performance of their interfacing system. Neural Interfaces implanted inside nerves of the stump offer the advantage of using the bidirectional neural pathways 'naturally' dispatching signals to control proper hand actions and feed-back sensations. Learning to control a neurally-interfaced hand prosthesis and decode sensory information was previously observed to reduce the inter-hemispheric asymmetry of cortical motor maps and the clinical symptoms of phantom limb syndrome. Methods: Electroencephalographic (EEG) data was analysed using Functional Source Separation (FSS), a semi-blind method that incorporates prior knowledge about the signal of interest into data decomposition to give access to cortical patch activities. Results: Bi-hemispheric cortices showed normalization of their activity (topographical and spectral patterns) and of functional connectivity between homologous hand controlling areas, during the delivery of the motor command to the cybernetic prosthesis. Conclusions: The re-establishment of central-peripheral communication with the lost limb induced by a neurally-interfaced hand prosthesis produces beneficial plastic reorganization, not only restructuring contralateral directly-connected control areas, but also their functional balance within the bi-hemispheric system necessary for motor control. and the integrity of cutaneous/proprioceptive sensory organs. Brain Machine Interfaces (BMI) bypass the above steps and allow motor signals to be picked up directly from the nervous system and relayed to an external electronic or robotic effector which physically performs the subject's motor intention and plans. In addition to facilitating extraction of motor volition, bidirectional BMIs also create the capacity to manage neural signal flows in both afferent and efferent directions.
The Journal of Physiology, 2007
A brain-computer interface (BCI) can be defined as any system that can track the person's intent ... more A brain-computer interface (BCI) can be defined as any system that can track the person's intent which is embedded in his/her brain activity and, from it alone, translate the intention into commands of a computer. Among the brain signal monitoring systems best suited for this challenging task, electroencephalography (EEG) and magnetoencephalography (MEG) are the most realistic, since both are non-invasive, EEG is portable and MEG could provide more specific information that could be later exploited also through EEG signals. The first two BCI steps require set up of the appropriate experimental protocol while recording the brain signal and then to extract interesting features from the recorded cerebral activity. To provide information useful in these BCI stages, our aim is to provide an overview of a new procedure we recently developed, named functional source separation (FSS). As it comes from the blind source separation algorithms, it exploits the most valuable information provided by the electrophysiological techniques, i.e. the waveform signal properties, remaining blind to the biophysical nature of the signal sources. FSS returns the single trial source activity, estimates the time course of a neuronal pool along different experimental states on the basis of a specific functional requirement in a specific time period, and uses the simulated annealing as the optimization procedure allowing the exploit of functional constraints non-differentiable. Moreover, a minor section is included, devoted to information acquired by MEG in stroke patients, to guide BCI applications aiming at sustaining motor behaviour in these patients. Relevant BCI featuresspatial and time-frequency properties -are in fact altered by a stroke in the regions devoted to hand control. Moreover, a method to investigate the relationship between sensory and motor hand cortical network activities is described, providing information useful to develop BCI feedback control systems. This review provides a description of the FSS technique, a promising tool for the BCI community for online electrophysiological feature extraction, and offers interesting information to develop BCI applications to sustain hand control in stroke patients.
NeuroImage, 2008
Sensory feedback in motor control is widely recognized to be the key link between the activity of... more Sensory feedback in motor control is widely recognized to be the key link between the activity of the primary motor cortex to the motor behavior.
Clinical Neurophysiology, 2010
Clinical Neurophysiology, 2010
Clinical Neurophysiology, 2010
Clinical Neurophysiology, 2011
Clinical Neurophysiology, 2010